System and method for turbulence detection

ABSTRACT

A aircraft hazard warning system or method can be utilized to determine a location of turbulence, hail or other hazard for an aircraft. The aircraft hazard warning system can utilize processing electronics coupled to an antenna. The processing electronics can determine an inferred presence of turbulence in response to lightning sensor data, radar reflectivity data, turbulence data, geographic location data, vertical structure analysis data, and/or temperature data. The system can include a display for showing the turbulence hazard and its location.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims the benefit of and priority to and is aContinuation of U.S. application Ser. No. 12/075,103, filed on Mar. 7,2008, entitled “SYSTEM AND METHOD FOR TURBULENCE DETECTION” by Woodellet al., and is incorporated herein by reference in its entirety now U.S.Pat. No. 8,902,100. U.S. patent application Ser. No. 11/370,085, filedMar. 7, 2006, now U.S. Pat. No. 7,515,087, U.S. patent application Ser.No. 11/402,434, filed Apr. 12, 2006, now U.S. Pat. No. 7,486,219, U.S.patent application Ser. No. 11/256,845, filed Oct. 24, 2005, now U.S.Pat. No. 7,598,902, and U.S. patent application Ser. No. 10/631,253filed Jul. 31, 2003, now U.S. Pat. No. 7,129,885 are herein incorporatedby reference in their entireties.

BACKGROUND

This application relates generally to the identification of turbulence.More particularly, this application relates to the identification ofturbulence by analysis of convective cells detected by aircraft hazardwarning systems.

Hazardous weather is generally associated with convective weather cells.Convective weather cells can produce turbulence, high winds, lightning,hail, and other weather hazards. With the large amount of air trafficand rising fuel costs, pilots are interested in identifying convectivecells (e.g., often hazardous weather) from non-convective cells (e.g.,stratiform rain) so they do not unnecessarily avoid flight routesthrough non-hazardous weather. Convective cells can also providedangerous and uncomfortable flight conditions for the crew andpassengers.

Lightning is generally caused when mixed state hydrometeors rub togetherin vertical shearing regions inside convective cells. Generally, cellsthat are producing lightning are turbulent and have the capacity toproduce hail. Therefore, the presence of lightning in a particular areacan be an indication of the presence of a convective cell or at least apotentially hazardous weather region.

Weather radar systems generally include an antenna, areceiver/transmitter circuit, a processor, and display. The processor iscoupled between the display and the receiver/transmitter circuit. Thereceiver/transmitter circuit is coupled between the processor and theantenna. The processor provides transmit signals through thereceiver/transmitter circuit to the antenna to transmit radar beams. Theprocessor receives radar return signals derived from radar returnsreceived by the antenna. The radar return signals are provided to theprocessor via the receiver/transmitter circuit.

Conventionally, pilots use weather radar systems to detect and avoidhazardous weather. The radar return signals are processed to providegraphical images to a radar display. The radar display is typically acolor display providing graphical images in color to represent theseverity of weather. Some aircraft systems also include other hazardwarning systems such as a turbulence detection system. The turbulencedetection system can provide indications of the presence of turbulenceor other hazards.

Conventional aircraft hazard weather radar systems, such as the WXR 2100MultiScan™ radar system manufactured by Rockwell Collins, Inc., haveDoppler capabilities and are capable of detecting four parameters:weather range, weather reflectivity, weather velocity, and weatherspectral width or velocity variation. The weather reflectivity istypically scaled to green, yellow, and red color levels that are relatedto rainfall rate. The radar-detected radial velocity variation can bescaled to a turbulence level and displayed as magenta.

Although radar-detected reflectivity and radar-detected velocityvariation are correlated to aircraft hazards, they may not provide acomplete picture to the pilot. For example, rainfall rates derived fromradar reflectivity data are generally related to the most visibleweather related advisory on the flight deck. However, heavy rain is notinherently hazardous to the aircraft. Heavy rain is displayed to theflight crew because it is often associated with true weather hazardssuch as lightning, hail, and turbulence.

Some weather radar systems incorporate turbulence detection functions.In areas of reasonably high reflectivity, conventional aircraft hazardwarning systems can detect variation in the velocity signatures withinthunderstorms. This velocity variation, or spectral width in radarterminology, is correlated to turbulence within the storm. Conventionalturbulence detection algorithms have limitations, however. Direct radarbased turbulence detection systems typically have a short range, forexample up to about forty or fifty nautical miles. Forty nautical milesis a relatively short distance when air crews are trying to maneuvernear storm cells. In addition, turbulence thresholds are typically setso high to adhere to regulatory agencies that the turbulence is onlyvisible in the cores of convective cells, areas which aircrews avoidanyway due to very high (red) reflectivity. A conventional turbulencedetector has generally been incapable of adjusting with respect togeographic location.

Thus, there is a need for a system and method for more accurate, longrange detection of turbulence. There is also a need for inferring theexistence of turbulence based on the detection and analysis ofconvective cells or hazards associated therewith. There is also a needto detect and locate turbulent weather cells as opposed tonon-turbulent, isolated cells. Further still, there is a need to detectand locate turbulent convective cells as opposed to non-turbulentconvective cells. Yet further, there is a need for a aircraft hazardwarning system optimized to determine the location and presence ofturbulent cells. Further, there is a need for a aircraft hazard warningsystem that includes more functions than a conventional rain gauge.

It would be desirable to provide a system and/or method that providesone or more of these or other advantageous features. Other features andadvantages will be made apparent from the present specification. Theteachings disclosed extend to those embodiments which fall within thescope of the appended claims, regardless of whether they accomplish oneor more of the aforementioned needs.

SUMMARY

One embodiment of the disclosure relates to an aircraft hazard warningsystem. The aircraft hazard warning system includes an input forreceiving lightning detection data, radar reflectivity data, turbulencedata, geographic location data, vertical structure analysis data, and/ortemperature data. The aircraft hazard warning system also includes aprocessing system for determining a presence of turbulence. Theprocessing system receives the lightning detection data, radarreflectivity data, turbulence data, geographic location data, verticalstructure analysis data, and/or temperature data. The processing systemperforms inferential turbulence detection in response to at least one ofthe lightning detection data, radar reflectivity data, turbulence data,geographic location data, vertical structure analysis data, andtemperature data.

Another embodiment of the disclosure relates to a method of displayingan indication of a hazard on an aircraft display in an avionics system.The method includes the step of receiving lightning detection data,radar reflectivity data, turbulence data, geographic location data,vertical structure analysis data, and/or temperature data. The methodalso includes the steps of receiving radar returns, providing a firstturbulence assessment in response to the radar returns, and providing aninferential turbulence detection assessment in response to the lightningsensor data, radar reflectivity data, turbulence data, geographiclocation data, vertical structure analysis data, and/or temperaturedata. The method also includes the step of providing the indicationusing the inferential turbulence detection assessment and the firstturbulence assessment.

Another embodiment of the disclosure relates to an apparatus fordetermining a presence of a hazard for an aircraft. The apparatusincludes means for providing a first turbulence assessment in responseto radar returns. The apparatus also includes means for providing aninferential turbulence detection assessment in response to lightningsensor data, radar reflectivity data, turbulence data, geographiclocation data, vertical structure analysis data, and/or temperaturedata. the apparatus also includes means for causing a display to providean indication of the presence of turbulence using the inferentialturbulence detection assessment and the first turbulence assessment.

Another embodiment relates to a aircraft hazard warning system. Thesystem includes an input for radar reflectivity data and temperaturedata, and a processing system. The processing system determines apresence of hail. The processing system receives the radar reflectivitydata, and the temperature data. The processing system determines a firstaltitude associated with the zero degree centigrade point and thepresence of hail when the reflectivity data indicates a reflectivity ata second altitude above the first altitude is above a first threshold.

Another embodiment relates to method of displaying an indication of ahazard on an aircraft display in an avionics system. The methodincluding receiving lightning detection data, radar reflectivity data,turbulence data, geographic location data, vertical structure analysisdata, and/or temperature data, providing a first turbulence assessmentin response to a spectral width parameter associated with the radarreturns, the method also includes providing an inferential turbulencedetection assessment in response to the lightning sensor data, radarreflectivity data, turbulence data, geographic location data, verticalstructure analysis data, and/or temperature data, and providing theindication using the inferential turbulence detection assessment and thefirst turbulence assessment.

Another exemplary embodiment relates to an apparatus for determining apresence of a convective cell or turbulence in an environment of anaircraft. The apparatus includes an input for radar reflectivity data,and a processing system for determining the presence of the convectivecell or turbulence. The processing system receives the radarreflectivity data and uses gradients in the radar reflectivity todetermining the presence of the convective cell.

Another exemplary embodiment relates to a aircraft hazard warningsystem. The aircraft warning system includes an input for radarreflectivity data, and a processing system for determining a presence ofturbulent bow wave in response to storm growth rate determined using thereflectivity data.

BRIEF DESCRIPTION OF THE DRAWINGS

The invention will become more fully understood from the followingdetailed description, taken in conjunction with the accompanyingdrawings, wherein like reference numerals refer to like elements, inwhich:

FIG. 1 is a block diagram of a hazard warning system according to anexemplary embodiment.

FIG. 2 is a functional flow diagram of various processes executed in thehazard warning system of FIG. 1 according to an exemplary embodiment.

FIGS. 3A and 3B are a more detailed version of the functional flowdiagram of FIG. 2 according to an exemplary embodiment.

FIG. 4 is a screenshot of the horizontal display in the functional flowdiagrams of FIGS. 3A and 3B according to an exemplary embodiment.

FIG. 5 is a screenshot of the vertical display in the functional flowdiagrams of FIGS. 3A and 3B according to an exemplary embodiment.

FIG. 6 is a chart showing errors corresponding to the verticalresolution of the hazard warning system of FIG. 1 according to anexemplary embodiment.

FIG. 7 is a chart illustrating how thunderstorm reflectivity may changebased on geographic location and/or height according to some exemplaryembodiments.

DETAILED DESCRIPTION OF THE EXEMPLARY EMBODIMENTS

Before describing in detail the particular improved system and method,it should be observed that the invention includes, but is not limited toa novel structural combination of conventional data/signal processingcomponents and communications circuits, and not in the particulardetailed configurations thereof. Accordingly, the structure, methods,functions, control and arrangement of conventional components software,and circuits have, for the most part, been illustrated in the drawingsby readily understandable block representations and schematic diagrams,in order not to obscure the disclosure with structural details whichwill be readily apparent to those skilled in the art, having the benefitof the description herein. Further, the invention is not limited to theparticular embodiments depicted in the exemplary diagrams, but should beconstrued in accordance with the language in the claims.

An aircraft hazard warning system or other avionic system may inferturbulence and change or adjust detection parameters as a function ofother sensor information and geographical location. The hazard warningsystem scales reflectivity with air temperature to better representhazards from convective cells at altitudes above the freezing layerwhere reflectivity tends to fall off. The weather hazards vary greatlywith geography. In some geographical regions, heavy rain may be typicalwhile convective activity that produces turbulence, hail, and lightningmay be rare. In other locations, storms rain out at low altitude andreflectivity at high altitude is very low even though the high altitudeturbulence above the convective area is still present. Satellite dataand worldwide test flight data may allow selection of display thresholdsto better characterize weather threats at different geographiclocations.

By providing better weather interpretation, the hazard warning systemmay infer true aircraft hazards such as hail, lightning, and turbulencefrom more basic sensor information. In the specific case of turbulence,the basic sensor information (e.g., radar measured spectral width) doesnot change with geographical location. The inferred turbulence, however,does change with geographical location.

The current regulatory environment as defined by governmental regulatoryagencies supports display of basic radar sensor information as red,yellow, and green for radar reflectivity calibrated to rainfall rate andmagenta as turbulence. The regulatory agencies do not currently provideguidance for changing the definition of the radar display based oninferred hazards. The radar display format may be selected to displayradar colors consistent with turbulence and rainfall rate as currentlydefined by regulatory authorities or as defined in the future by suchauthorities. A hazard assessment indication can be provided in a mannerthat does not interfere with display of standard weather data.

Referring to FIG. 1, a weather radar system or hazard warning system 10includes sensor inputs 12, a processor 14, a display 16, a user input18, and a memory 20. Hazard warning system 10 may acquire horizontaland/or vertical reflectivity profiles and direct turbulence detectioninformation via sensor inputs 12. Sensor inputs 12 generally include aradar antenna 22, a lightning detector 24, and a temperature sensor 26.According to other exemplary embodiments, sensor inputs 12 may includeany type of sensor or detector that may provide data related to director inferred measurement or detection of weather conditions and/orhazards.

Lightning detector 24 may be an airborne lightning sensor that providespolarity, strike rate, range, bearing, strike strength, lightning type(e.g., cloud to cloud, cloud to ground, etc.), and rate history for eachlightning flash relative to the aircraft. Detector 24 can derive a rangeinterval from the amplitude information. Lightning detector 24 is alightning sensor that can be integrated within system 10 or be aseparate unit from system 10. Lightning detector 24 can be aboard theaircraft associated with system 10 or can be an onboard systemcommunicating wirelessly with system 10.

Alternatively, lightning data can be provided from ground based systemsor other systems not aboard the aircraft. The lightning data can becorrelated with respect to the preset location of the aircraft forcomparison with other weather data sensed by other sensors, such asweather radar systems, optical sensors, etc.

Detector 24 preferably provides lightning data indicative of thepresence and/or location of lightning strikes. The lightning data can beraw data from detector 24 or processed data that indicates a locationand presence for each lightning strike and the rate of lighting strikesin a given cell. In one embodiment, the lightning data points toward orindicates the bearing of detected lightning strikes. The lightningsensor may also provide inferential information related to turbulenceand/or hail.

Lightning detector 24 is preferably a Storm Scope™ lightning sensor,narrow band optical imaging system, or other sensor for determining thepresence of lightning strikes. Detector 24 preferably also provides abearing to lightning strikes and an estimated location of lightningstrikes. Detector 24 may also provide lightning strike rate, polarity oflightning strike and lightning strike type: cloud-to-ground,cloud-to-cloud, etc. In one example, the lightning detector can be anLD-250 lightning detector configured for communication with detectorprocessor 14.

In one embodiment, detector 24 provides the data in range and azimuthform to processor 14 indicating the location and presence of lightningstrikes or at least the bearing from the aircraft to the lightningstrike. Alternatively, processor 14 can obtain raw data from lightningdetector 24 and determine presence and location of lightning strikesfrom the raw data.

Detector 24 can be a detector purchased from Boltek Company or L3modified to be used with system 10. In one embodiment, detector 24 issimplified by only providing angle to lightning strike information sothat detector 24 can be of a simpler and less expensive wideband ADFdesign.

An antenna for detector 24 can be located at a base of a pedestal boomand utilize the pedestal power associated with aircraft hazard warningsystem 10 and its interface to a remote or wireless radar transceivercircuit. In addition, the antenna for detector 24 can use the currentweather radar mechanical pedestal structure associated with radarantenna 22.

The hybrid approach of hazard warning system 10 correlates radarreflectivity and lightning data to overcome the shortcomings of thelightning strike inaccuracy. The hybrid approach determines lightningstrike position relative to radar reflectivity measurements, withsufficient accuracy, to make a convective assessment on a weather event.

Processor 14 is generally configured to process data received fromsensor inputs 12 to determine a hazard threat level, receive input fromuser input 18, and provide hazard indication on display 16. Processor 14includes turbulence detector 28, inferred turbulence detector 29, andcell tracker 30. Processor 14 can generate a velocity parameter 32 orother Doppler data, a spectral width parameter 34, a reflectivityparameter 36, and a range parameter 38 based on return data from sensorinputs 12, data or commands from user input 18, or data or instructionsfrom memory 20. According to various exemplary embodiments, processor 14can be any hardware and/or software processor or processing architecturecapable of executing instructions and operating on data related tohazard detection. According to various exemplary embodiments, memory 20can be any volatile or non-volatile memory capable of storing dataand/or instructions related to hazard warning system 10.

Direct turbulence detector 28 is configured to provide turbulence databased on a direct measurement of spectral width, for example spectralwidth parameter 34, from radar antenna 22. A large spectral widthcorresponds to turbulence. Direct turbulence detector 28 can provide aturbulence hazard indication on display 16.

Inferred turbulence detector 29 is configured to provide inferred orunmeasured turbulence data using measured data. Inferred turbulencedetector 29 can receive data inputs derived from one or more of spectralwidth parameter 34, reflectivity parameter 36, and/or range parameter38.

Inferred turbulence detector 29 can also receive temperature data fromtemperature sensor 26 and data from lightning detector 24. Temperaturedata can include a local atmospheric temperature, local temperaturevariations with time, local temperature variations with altitude, aremotely determined temperature, and/or remotely determined temperaturegradients in either range or altitude.

The detection of lightning generally indicates the presence of aconvective call and of turbulence within the cell. Detection of a singlelightning bolt can infer the presence of turbulence. The use oflightning history data may provide a more accurate inferred turbulenceassessment. If lighting history indicates a high lighting strike rate ina given cell the probability of turbulence with high magnitude withinthat cell is high.

Reflectivity parameter 36 can include data related to area reflectivity,gradient reflectivity, magnitude reflectivity, reflectivity shape,and/or a sharp change in reflectivity. Very high gradients (e.g., rapidchanges from red to black to yellow) can indicate the presence of aconvective cell and thus turbulence. According to one exemplaryembodiment, the very high gradient may be a change in cell reflectivitywithin a few range bins (e.g., one nautical mile). According to anotherexemplary embodiment, the very high gradient may be a change in cellreflectivity within three nautical miles.

If a cell is detected to be growing at a very high rate, it may be aconvective cell containing turbulence. If a cell is detected that hasgrown at a very high rate in the past, the cell may be convective andcontain turbulence. For example, the growth may be detected by avertical structure analysis. The vertical structure analysis data mayinclude vertical height, vertical growth rate, a vertical historyassessment, an assessment of whether the aircraft path will intersect aportion of a weather cell, and/or cell maturity data.

Inferred turbulence detector 29 can process at least one of parameters34, 36, 38 and/or data from detector 24 to provide a turbulence hazardindication on display 16. In addition, inferred turbulence detector 29can cause system 10 to perform further analysis in response toinformation from lightning detector 24 and/or a parameter 34, 36, 38.The further analysis can even include causing system 10 to performweather radar queuing and control in elevation and azimuth as well asexamining new data or historical data. Inferred turbulence detector 29can provide inferred turbulence data at longer ranges from measurementsthat are not directly turbulence related than direct turbulence detector28. Advantageously, detector 29 allows system 10 to provide notice ofturbulence at both short ranges (e.g., within 25 nmi, within 40 nmi,within 50 nmi, etc.) and long ranges (e.g., greater than 25 nmi, greaterthan 40 nmi, greater than 50 nmi, up to 75 nmi, up to 100 nmi, up to 320nmi, etc.). Detector 29 merges turbulence analysis from directdetections and inferred detections to give an overall awareness ofturbulence throughout the range of system 10.

Threat descriptions on display 16 can include lightning, hail, andturbulence. All three hazards can have substantial impact on airlineoperations. In one embodiment, the display of turbulence and potentiallightning may be paired with entire cells and circled by a line of thenormal turbulence color at lower levels of hazard. Regions of likelylightning and directly measured turbulence may use either a solid secondlevel turbulence color or be encoded with an icon. Preferably, display16 allows slewing from the full cell identification of convectiveweather at long ranges to a shorter range sub-cell size regions oflikely hazard.

After acquiring data from sensor inputs 12, processor 14 may use avariety of processing techniques to assess the weather hazard level.Processor 14 may identify and track relevant weather cells via celltracker 30. The cells may be prioritized in terms of their threat to theaircraft and detailed vertical scans can be conducted on high prioritytargets.

Conventional radar systems scale return power to display color withoutregard to the nature of the weather target being scanned. In contrast,hazard warning system 10 scales its return power system with respect toa height above the freezing layer as well as by geographic location. Atlow altitudes, liquid precipitation may produce very high radarreflectivity. As altitude increases, the temperature and correspondingradar reflectivity generally undergo a decrease. At cruise altitudeswhere hazard warning system 10 is primarily scanning ice crystals, theradar reflectivity may drop two or more color levels or disappearentirely from the display. Processor 14 uses outside air temperaturemeasurements to estimate height relative to the freezing layer wherehighly reflective water droplets change to more poorly reflective icecrystals. Processor 14 can automatically modify the display colorthresholds to provide a more uniform measure of the atmospheric moisturecontent regardless of whether the moisture occurs as ice or liquidwater.

Weather cell reflectivity also varies with geographical location. Forexample, equatorial oceanic weather cells tend to have significantlydifferent characteristics than continental and convective land basedweather. Oceanic cells on the average have 23 dBZ (two and ½ colorlevels) less reflectivity at cruise altitudes than equivalent land basedcells. This translates to only 1/200th as much radar echo from oceanicweather as compared to weather over land. This difference causes oceanicweather to be essentially invisible to conventional radar systems atcruise altitudes even though turbulence hazards may still exist high ina convective cell or storm.

Though the weather cell reflectivity varies with geographical location,the hazards associated with convective activity remain similar acrossthe world. Processor 14 compensates for localized weather reflectivityprofiles by automatically modifying operating parameters (e.g., antennabeam tilt, color thresholds, etc.) based on aircraft position data.These adjustment techniques complement existing government regulatorydocumentation that defines color levels based on rainfall rate. Sincethe hazard warning system 10 compensates weather trends due togeographical location, it provides a more accurate assessment of theatmospheric moisture content and thus, a more accurate representation ofthe weather threats.

Knowing the vertical extent of a weather cell can aid a pilot's decisionwhether to proceed through, or maneuver around a cell. Weather cell topsgenerally produce weak radar returns. Conventional radars sample weathercell tops using radar beams that are large in diameter with respect tothe vertical accuracies desired. These two constraints may require aradar design that carefully optimizes the sampling in the upper regionsof storm cells.

Some radars have used a multi-elevation process to estimate the verticalcharacteristics of weather cells. In order to minimize latency thismultiple bar method may only perform a few horizontal scans separated byseveral degrees and still spend most of its time scanning empty space.The coarse spacing in elevation that produces acceptable latenciesprovides poor vertical accuracy when mechanized to detect storm top andstorm growth.

Hazard warning system 10 may surpass the limitations of themulti-elevation process by separating the horizontal and verticalscanning and assessment process. Hazard warning system 10 mayautomatically identify weather cells and direct dedicated, fullystabilized vertical scans for each tracked weather cell to provide ahigh resolution assessment of each cell's vertical extent. Weather cellvertical scans may be prioritized based on their threat to the aircraft.Flight path segments, aircraft track angle, and/or pilot directed scanangles may be similarly scanned and estimated. Weather cells and anyflight path or pilot commanded headings may be continuously rescanned toprovide timely information.

In addition to direct reflectivity and turbulence data, hazard warningsystem 10 can utilize lightning detector 24 to directly sense lightningthreats to the aircraft. Conventional airborne lightning sensors aregenerally proficient at detecting the direction of the electricaldischarges, but are generally poor at determining range to thedischarge. Since lightning is typically associated with convectiveweather cells, processor 14 can identify regions of reflectivity alongthe heading indicated by lightning detector 24 and correct the lightningsensor range estimates to the nearest convective cells.

Processor 14 uses the presence of lightning to infer information abouthail. Weather cells that do not have enough updraft energy to producelightning typically do not produce hail. According to another exemplaryembodiment, radar return strength combined with temperature and altitudeinformation can be used to infer hail. If a height of 1.4 km above thezero degree centigrade point in the atmosphere has radar reflectivitygreater the 45 dBz, hail formation may be likely. Thetemperature/altitude algorithm may be used to infer both the likelihoodof hail and the likely maximum hail diameter.

The presence of lightning within a weather cell may be sufficient toidentify the cell as turbulent. Lightning is the result of atmosphericcharge separation. The charge separation occurs as the result offriction between particles in regions of strong, turbulent, and/orshearing winds. Since lightning can be detected and correlated withstorm cells at ranges of 100 miles or more, lighting detection can beused as an inferential turbulence indicator at ranges beyond the abilityof radars using only conventional spectral width estimates.

Referring to FIG. 2, a radar processing functional flow 100 of hazardwarning system 10 is illustrated. The display 16 is divided into ahorizontal view 102 and a vertical view 104. The two independent views102, 104 may include independent mode, range, and gain parameters.

The weather depiction on horizontal view 102 includes color patternsconsistent with typical rainfall rate displays except the radarreflectivity is corrected to normalized atmospheric moisture content asdescribed previously. Turbulence is sensed based on radar spectral widthand scaled to aircraft RMS vertical load.

A hazard estimation 110 is generated from the sum or other combination112 of the data outputs from measured and inferred functions includingdirect turbulence detection (process 108), reflectivity measurement(process 106), lightning and inferred turbulence measurement (process116), hail probability assessment (process 116), and/or storm growthassessment (process 118 and process 114) in order to generate an overallhazard assessment at each horizontal location. Each of the measurementsor assessments from processes 106, 114, 116, and 118 may individually orin any combination provide an assessment of an inferred turbulencehazard. The assessment can be depicted on horizontal view 102 as an iconor as a specific color. The icon may be transparent to the underlyingred/yellow/green radar display and capable of being turned off. Otherexemplary embodiments may include textual blocks depicting tops oftracked storm cells and/or dithered regions that alert the crew tostorms growing into the flight path (e.g., predictive overflight).

The hazard assessment display can be any combination (e.g., linear ornonlinear combination) of all the inputs. Alternately, each individualhazard component (e.g., lightning, inferred turbulence, directturbulence, inferred hail, etc.) may be displayed individually.

Hazard warning system 100 identifies storm cells (process 114) and mayautomatically direct vertical scan commands 146 toward the cells inorder to better assess the convective nature, maturity, and/orprobability of the aircraft intercepting the cell top or turbulent bowwave above the cell (process 118). Process 114 prioritizes the directedvertical scan commands 146 based on the threat to the aircraft. Thefactors considered in cell prioritization may include crew selectedvertical scan or automated directed scan history, cell reflectivity,cell hazard potential, cell proximity to the aircraft, cell proximity tothe current track, cell proximity to the FMS flight path, etc.

The cell prioritization may be applicable to automatically directedvertical or horizontal scans. A vertical scan associated with the crewselected vertical scan (e.g., vertical scan command 120) may be thehighest priority vertical function.

Vertical view 104 shows vertical cutsets along the flight plan, trackangle, and/or crew commanded azimuth angle (process 114) as a result ofthe crew selecting a vertical scan command 120. The colors generallyrepresent rainfall rate with reflectivity scaled to atmospheric moisturecontent in the same way as in horizontal view 102. Other exemplaryembodiments may include an icon depiction of storm top uncertaintyand/or an icon arrow that shows growth rate.

Referring to FIGS. 3A and 3B, a more detailed version of radarprocessing functional flow 100 of FIG. 2 is illustrated. In thegeographic weather correlation process 106, the tilt of radar antenna 22may be controlled (step 122). The power of the radar returns fromantenna 22 are computed (step 124) and corrected for reflectivityfalloff (step 126), for example due to elevation above a freezing layeror geographic location as shown in chart 500 of FIG. 7 or chart 600 inFIG. 8. Return power for multiple antenna 22 tilts is compared tosuppress ground clutter and false returns (step 128). The radar power iscorrected for range (step 130) and an overflight protection algorithm isrun (step 132) that retains power data at specified ranges, for exampleless than ten nautical miles. Based on the overflight protection data(step 132) and the corrected power (step 130), color thresholds areapplied based on regulatory specifications (step 134), as describedabove, for display on horizontal view 102 and for output as areflectivity assessment to data combination 112. Cell area andreflectivity gradient are assessed (step 135) in order to generate andinferred turbulence assessment which is provided to data combination112.

In the turbulence detection process 108 (e.g., direct turbulencedetection), the computed return power (step 124) is used to compute thespectral width of the return (step 136). The spectral width is used toestimate the turbulence in units scaled to the aircraft RMS verticalload (step 138). Color thresholds are applied to the turbulence estimatebased on regulatory specifications (step 140), for display on horizontalview 102 and for output as a turbulence assessment to data combination112.

The vertical weather assessment process 114 tags and tracks individualstorm cells (step 142) based on the corrected power from the geographicweather correlation process (step 130). The storm cells are prioritizedbased on the threat to the aircraft (step 144). Based either on a manualvertical scan command or an automatic scan command, system 10 performs avertical scan along a cell range and bearing (step 146). If the verticalscan was manually commanded by the crew (step 120) the vertical scandata is output to vertical view 104 for display and use by the crew. Ifthe vertical scan was an automatic scan, the data is also output to thelightning/hail threat assessment process 116. The vertical scan data isalso used to identify the top of the storm cell (step 148).

Lightning/hail threat assessment process 116 uses lightning detector 24to gather lightning data. The range of detector 24 is corrected based onradar reflectivity considerations (step 150). The range-corrected datais output to data combination 112 as a direct lightning detection and/oran inferential turbulence detection assessment. The automatic scanoutput data (step 146) is used to estimate the reflectivity at aspecified distance above or below the freezing layer (step 152), forexample 1.4 km above the freezing layer. Based on the reflectivityestimate (step 152) and the corrected data (step 150), system 10 makesan estimate of hail probability (step 154). The probability decision isat an unknown state by default and may change to a state of highprobability if the reflectivity estimate is greater than a predeterminedthreshold, for example if the reflectivity estimate 1.4 km above thefreezing layer is greater than 45 dbZ. If there is no lightning detectedthe hail probability changes to a low probability state. The estimatedhail probability is output as an inferential hail assessment to datacombination 112.

Storm top analysis process 118 uses the identified cell storm top data(step 148) and identifies the storm growth rate (step 156). The stormgrowth rate data is output as a storm maturity assessment to the datacombination 112 and used to estimate the height of a turbulent bow waveassociated with the storm cell (step 158). System 10 then estimates theprobability that the aircraft flight path will intersect the turbulencebow wave or storm cell (step 160) and outputs the estimate as apredictive overflight assessment to combined data 112.

Hazard estimation 110 is generated from the sum or other combination 112of the measured and inferential data to generate an overall weatherhazard assessment. The assessment can be depicted on horizontal view 102as an icon or specific color. The icon may be transparent to theunderlying red/yellow/green radar display and capable of being turnedoff. Other exemplary embodiments may include textual blocks depictingtops of tracked storm cells and/or dithered regions that alert the crewto storms growing into the flight path (e.g., predictive overflight).

According to an exemplary embodiment, combination 112 operates as alogical OR function with respect to inferred turbulence determined froma radar reflectivity measurement, lightning measurement, hailprobability assessment, storm growth or vertical structure analysisassessment, geographic location data, and/or temperature data.Alternatively, any combination 112 can operate as a logical AND functionwith respect to certain types of assessments or parameters, certaintypes of assessments or parameters at certain ranges, or certain typesof assessments or parameters at certain altitudes. These and otherlogical functions (e.g., NOR, NAND, XOR, etc.) can be combined in anymanner to provide the most appropriate inferred turbulence indication.

Cell reflectivity, after being compensated for temperature at altitudeand geographical location, may be used for cell identification andtracking According to one exemplary embodiment, the cell trackingalgorithm may store and/or track about 32 individual cells. According toother exemplary embodiments, more or fewer than 32 individual cells maybe stored and/or tracked.

Cell reflectivity may be used in cell hazard assessment but otherfactors such as presence of lightning, presence of turbulence,probability of hail, storm maturity, storm growth, and/or verticalextent from previous vertical scans may also be included.

Highly reflective cells within about twenty nautical miles of theaircraft may be relevant regardless of where they lie relative to theaircraft flight path or heading. Tactical decisions may force the crewto deviate from the flight path and the crew should have the bestavailable short range radar to support these tactical maneuvers.

Beyond twenty nautical miles, highly reflective cells may be prioritizedbased on their proximity to the current track out to the limits of thecurrent flight plan segment. If the current track shows significantlateral deviation from the FMS flight plan, cells can be reprioritizedbased on current track angle rather than flight plan angle. Highlyreflective cells may be prioritized based on their proximity to flightpath segments beyond the current flight segment.

Though the vertical scans (both automatic and manual) may provide usefultactical information, the vertical functions do have limitations. Ingeneral, the resolution of the vertical data being collected anddisplayed may have an error rate that increases with range. Threeprimary errors affect the radar's ability to accurately determine stormheight: error due to beamwidth, error between tilt samples, and errordue to the difference between radar detectible storm top and turbulentbow wave.

The 3 db two way beamwidth of an air transport class radar antenna isapproximately 2.7 degrees. This angular width means the vertical heightof the beam spreads with range so the height estimation error alsoincreases with range. If the nature of a radar target is unknown, theresolution error may be R*tan(2.7 deg) where R is the range. Since thenature of the target along with the antenna beam shape is generallyknown, the vertical resolution can be increased by a technique calledbeam deconvolution; the beam shape may be divided out of the sensedradar measurement. Beam deconvolution may allow vertical resolution tobe improved by a factor of two, reducing the resolution error due tobeamwidth to about 0.5*R*tan(2.7 deg).

Additional range-dependent error may be present due to the radarvertical sampling interval. Hazard warning system 10 performs verticalassessments at ⅛ degree intervals, which may results in a peak to peakvertical error of R*tan(0.125 deg).

The radar may not be capable of directly detecting clear air hazardsabove convective cells. Significant turbulence may be experienced ashigh as 1500 meters above the radar-detectible storm top with an averageclear air turbulence height of about 950 meters above the radar top.Even if an average estimate of 950 meters is added to the displayedstorm top to account for the average height of the clear air turbulence,variation in clear air turbulence estimates result in a peak to peakvariance of about 900 meters.

According to various exemplary embodiments, the process flow of FIGS. 2,3A, and 3B may be embodied as hardware and/or software. In exemplaryembodiments where the processes are embodied as software, the processesmay be executed as computer code on any processing or hardwarearchitecture or in any weather radar system such as the WXR-200available from Rockwell Collins.

Referring to FIG. 4, a screenshot 200 of horizontal view 102 providesreflectivity scaled as moisture content and turbulence scaled to RMSvertical load according to an exemplary embodiment. The moisture contentmay be illustrated by the colors green, yellow, and red (represented bythe legend in the FIG) and both directly measured and/or inferredturbulence may be represented as another color such as magenta.Alternatively, inferred turbulence may be represented differently thandirectly measured turbulence. In one exemplary embodiment, inferredturbulence may be the same color as directly measured turbulence, butthe inferred turbulence indication may be stippled or cross-hatched.According to another exemplary embodiment, the inferred turbulence maybe of a different color than the directly measured turbulence.

Referring to FIG. 5, a screenshot 300 of vertical view 104 providesvertical reflectivity scaled as moisture content (e.g., green, yellow,and red) according to an exemplary embodiment. Screenshot 300 shows thevertical profile of two example storms with heights of 20000 and 42000feet over a distance of about 60 nautical miles. The lower dashed lineacross screenshot 300 gives an estimated minimum altitude for anaircraft to fly to avoid terrain hazards.

FIG. 6, shows a chart 400 of a stack up of peak-to-peak verticalresolution errors of directly measured cell height as a function ofrange and the associated root-sum-square (RSS) of the error. The errorstack up increases with range to a degree that the inferred cell heighthas higher accuracy than the directly measured system. Chart 400accounts for beamwidth resolution 402, sample resolution 404, and clearair turbulence (CAT) 406 above convective cells. At 40 nmi, an RSSresolution error of +/−1000 meters (2000 meters peak to peak) may beexpected. At 100 nmi, this resolution error grows to +/−2250 meters(4500 meters peak to peak).

Referring to FIG. 7, a chart 500 illustrates how storm or convectivecell reflectivity can change based on geographic location and/or heightor elevation according to an exemplary embodiment (Zipser, E. J. andLutz, K. R., “The Vertical Profile of Radar Reflectivity of ConvectiveCells,” American Meteorological Society, Volume 122, Issue 8, August1994). For example, oceanic thunderstorms or convective cells may haveless reflectivity at a given temperature altitude than storms orconvective cells in Europe, while storms and convective cells in Europemay have less reflectivity at a given temperature altitude than those inthe continental United States. A storm or cell may also have lessreflectivity at a higher elevation and greater reflectivity at a lowerelevation.

The temperature altitude may be the altitude at which a giventemperature is found. For example, lightning likely exists at midlatitudes when radar reflectivity exceeds 35 dBz at the altitude wherethe temperature falls to −15 degrees centigrade. This may be called the−15 degree temperature altitude. A specific reflectivity at an altitudewhere the temperature is at or below the freezing level may indicate thepresence of a convective cell and thus turbulence.

While the detailed drawings, specific examples, detailed algorithms andparticular configurations given describe preferred and exemplaryembodiments, they serve the purpose of illustration only. The inventionsdisclosed are not limited to the specific forms shown. For example, themethods may be performed in any of a variety of sequence of steps oraccording to any of a variety of mathematical formulas. The hardware andsoftware configurations shown and described may differ depending on thechosen performance characteristics and physical characteristics of theweather radar and processing devices. For example, the type of systemcomponents and their interconnections may differ. The systems andmethods depicted and described are not limited to the precise detailsand conditions disclosed. The flow charts show preferred exemplaryoperations only. The specific data types and operations are shown in anon-limiting fashion. Furthermore, other substitutions, modifications,changes, and omissions may be made in the design, operating conditions,and arrangement of the exemplary embodiments without departing from thescope of the invention as expressed in the appended claims.

What is claimed is:
 1. A method of displaying an indication of a hazardon an aircraft display using an avionics warning system, the methodcomprising: sensing presence of lightning using a lightning sensor toprovide lightning detection data; providing a first turbulenceassessment in response to a spectral width parameter associated withradar returns output from an airborne radar antenna using the avionicswarning system; providing an inferential turbulence detection assessmentin response to the lightning detection data using the avionics warningsystem; and providing the indication using the inferential turbulencedetection assessment and the first turbulence assessment using aprocessing system in the avionics warning system.
 2. The method of claim1, wherein the avionics warning system determines one or more of: atarget range, Doppler velocity information, a Doppler derived spectralwidth parameter, an area reflectivity parameter, a gradient reflectivityparameter, vertical structure, and a magnitude reflectivity parameterusing the radar returns, wherein the inferential turbulence detectionassessment is provided using the one or more of: the target range,Doppler velocity information, Doppler derived spectral width parameter,area reflectivity parameter, gradient reflectivity parameter, verticalstructure, and magnitude reflectivity parameter.
 3. The method of claim1, wherein the lightning detection data includes one or more of:lightning polarity, lightning strike rate, lightning strike range,lightning strike bearing, lightning strike strength, lightning type, andlightning rate history.
 4. The method of claim 1, wherein the avionicswarning system receives atmospheric temperature data including one ormore of: local temperature, local temperature variations with time,local temperature variations with altitude, remotely determinedtemperature, and remotely determined temperature gradients in eitherrange or altitude and wherein the processing system uses the atmospherictemperature data to provide the inferential turbulence detectionassessment.
 5. The method of claim 1, wherein the avionics warningsystem provides vertical structure analysis data in response to theradar returns, the vertical structural analysis data being used toprovide the inferential turbulence detection assessment and includingone or more of: vertical height, vertical growth rate, vertical historyassessment, assessment of whether the aircraft path will intersect aportion of a weather cell, and cell maturity.
 6. The method of claim 1,further comprising providing a predictive overflight assessment andproviding the indication if the predictive overflight assessmentindicates that the hazard is above a flight path of an aircraftassociated with the aircraft display.
 7. The method of claim 6, whereinthe hazard is a turbulence hazard.
 8. An aircraft hazard warningapparatus for determining a presence of a convective cell or turbulencein an environment of an aircraft, the apparatus comprising: a weatherradar antenna for receiving radar returns; and an electronic processingsystem for determining the presence of the convective cell orturbulence, the processing system using radar reflectivity dataassociated with the radar returns received by the radar antenna, theprocessing system using gradients in the radar reflectivity data todetermine the presence of the convective cell or turbulence, wherein thepresence is determined when the gradients are very high gradients,wherein the very high gradients are associated with the radarreflectivity data indicating a change of one range of reflectivitycorresponding to a first color displayed on a display to another rangeof reflectivity corresponding to a second color displayed on thedisplay, wherein an intermediate range is between the first range andthe second range and corresponds to a third color displayed on thedisplay, the change being within a few range bins.
 9. An aircraft hazardwarning apparatus for determining a presence of a convective cell orturbulence in an environment of an aircraft, the apparatus comprising: aradar antenna for receiving radar returns; and an electronic processingsystem for determining the presence of the convective cell orturbulence, the processing system receiving radar reflectivity dataassociated with the radar returns received by the radar antenna, theprocessing system using gradients in the radar reflectivity data todetermining the presence of the convective cell or turbulence, whereinthe presence is determined when the gradients are very high gradients,wherein the very high gradients are associated with the radarreflectivity data indicating a change of one range of reflectivitycorresponding to a first color displayed on a display to another rangeof reflectivity corresponding to a second color displayed on thedisplay, wherein an intermediate range is between the first range andthe second range and corresponds to a third color displayed on thedisplay, the change being within one nautical mile.
 10. An aircrafthazard warning system for determining a presence of turbulence,comprising: a radar antenna for receiving radar returns; and an onboardelectronic processing system in communication with the radar antenna andconfigured to receive the radar returns from the radar antenna and todetermine the presence of the turbulence in response to an inferentialturbulence assessment and a direct turbulence assessment, the processingsystem being configured to use a spectral width parameter associatedwith the radar returns received by the radar antenna for the directturbulence assessment, the processing system using a radar reflectivityparameter associated with the radar returns for the inferentialturbulence assessment.
 11. The system of claim 10, wherein a stormgrowth rate is used to determine storm maturity for the inferentialturbulence assessment, wherein the inferential turbulence assessmentestimates a height of a bow wave using the storm maturity.
 12. Thesystem of claim 10, wherein the processing system determines one or moreof: a target range, Doppler velocity information, a Doppler derivedspectral width parameter, an area reflectivity parameter, a gradientreflectivity parameter, vertical structure, and a magnitude reflectivityparameter using the radar returns, wherein the inferential turbulenceassessment is provided using the one or more of: the target range,Doppler velocity information, a Doppler derived spectral widthparameter, an area reflectivity parameter, a gradient reflectivityparameter, vertical structure, and a magnitude reflectivity parameter.13. The system of claim 10, wherein the processing system uses lightningsensor data including one or more of: lightning polarity, lightningstrike rate, lightning strike range, lightning strike bearing, lightningstrike strength, lightning type, and lightning rate history.
 14. Thesystem of claim 10, wherein the processing system receives atmospherictemperature data including one or more of: local temperature, localtemperature variations with time, local temperature variations withaltitude, remotely determined temperature, and remotely determinedtemperature gradients in either range or altitude and wherein theprocessing system uses the atmospheric temperature data to provide theinferential turbulence detection assessment.
 15. A method of displayingan indication of a hazard on an aircraft display using an avionicssystem in response to radar returns associated with an airborne radarantenna, the method comprising: receiving the radar returns on theairborne radar antenna; providing a first turbulence assessment inresponse to a spectral width parameter associated with the radarreturns; providing an inferential turbulence detection assessment inresponse to radar reflectivity data associated with the radar returnsand temperature data; and providing the indication using the inferentialturbulence detection assessment and the first turbulence assessment inan electronic processing system.
 16. The method of claim 15, wherein theprocessing system determines one or more of: a target range, Dopplervelocity information, a Doppler derived spectral width parameter, anarea reflectivity parameter, a gradient reflectivity parameter, verticalstructure, and a magnitude reflectivity parameter using the radar returndata.
 17. The method of claim 15, wherein the processing system useslightning sensor data for the inferential turbulence detectionassessment including one or more of: lightning polarity, lightningstrike rate, lightning range, lightning bearing, lightning strikestrength, lightning type, and lightning rate history.
 18. The method ofclaim 15, wherein the processing system uses atmospheric temperaturedata for the inferential turbulence detection assessment including oneor more of: local temperature, local temperature variations with time,local temperature variations with altitude, remotely determinedtemperature, and remotely determined temperature gradients in eitherrange or altitude.
 19. The method of claim 15, wherein the processingsystem uses vertical structure analysis data for the inferentialturbulence detection assessment including one or more of: verticalheight, vertical growth rate, vertical history assessment, assessment ofwhether the aircraft path will intersect a portion of a weather cell,and cell maturity.
 20. The method of claim 15, further comprisingproviding a predictive overflight assessment and providing theindication if the predictive overflight assessment indicates that thehazard is above a flight path of an aircraft associated with theaircraft display.
 21. The method of claim 15, wherein the hazard is aturbulence hazard.